Entrepreneurial success factors: An exploratory study based on Data Mining Techniques

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María Messina
Esther Hochsztain

Abstract

Since 2007, the CCEE Entrepreneurship Centre has developed a supporting program for entrepreneurs. A preliminary analysis to determine if the venture was successful or a failure is made to improve the program’s management . In this article, the authors identify the main factors associated with entrepreneurship’s success, and how they can anticipate entrepreneurship’s performance. The case study is based on a survey data applied to the Entrepreneurship Program participants. The two data mining techniques are decision trees and logistic regression. The results were consistent across both tech- niques. The findings show that the two most important elements to predict entrepreneurship’s success are fun- ding and previous experience as self-employed. The results provided very useful insight about the best ways to support entrepreneurship, how to encoura- ge entrepreneurs, and define tools or activities to impact positively ventures success in Uruguay, since similar stu- dies have not been developed.

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How to Cite
Messina, M., & Hochsztain, E. (2015). Entrepreneurial success factors: An exploratory study based on Data Mining Techniques. Tec Empresarial, 9(1), Pág. 30–40. https://doi.org/10.18845/te.v9i1.2206
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